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ACL
2009
13 years 7 months ago
Markov Random Topic Fields
Most approaches to topic modeling assume an independence between documents that is frequently violated. We present an topic model that makes use of one or more user-specified grap...
Hal Daume III
PAMI
1998
103views more  PAMI 1998»
13 years 9 months ago
Synchronous Random Fields and Image Restoration
—We propose a general synchronous model of lattice random fields which could be used similarly to Gibbs distributions in a Bayesian framework for image analysis, leading to algor...
Laurent Younes
JCB
2006
215views more  JCB 2006»
13 years 9 months ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
EMMCVPR
1999
Springer
14 years 1 months ago
Auxiliary Variables for Markov Random Fields with Higher Order Interactions
Markov Random Fields are widely used in many image processing applications. Recently the shortcomings of some of the simpler forms of these models have become apparent, and models ...
Robin D. Morris
EMNLP
2009
13 years 7 months ago
On the Use of Virtual Evidence in Conditional Random Fields
Virtual evidence (VE), first introduced by (Pearl, 1988), provides a convenient way of incorporating prior knowledge into Bayesian networks. This work generalizes the use of VE to...
Xiao Li